Intelligent-assistant system for scleral spur location.

A system based on the use of two artificial neural networks (ANNs) to determine the location of the scleral spur of the human eye in ocular images generated by an ultrasound biomicroscopy is presented in this paper. The two ANNs establish a relationship between the distance of four manually placed landmarks in an ocular image with the coordinates of the scleral spur. The latter coordinates are generated by the expert knowledge of a subject matter specialist.

Acquisition of skin characteristics by Monte Carlo modeling and evolutionary setting of parameters.

Background: In this paper, we present the intelligent system to characterize optically human skin; our proposal is a non-invasive way to obtain some parameters of the skin such as the concentration of hemoglobin, water percentages, and thickness of the layers of the skin.

Material And Methods: To achieve the objective of this work, we used an experimental technique called diffuse reflectance spectrophotometry and numerical calculations, such as the Monte Carlo method and the evolutionary algorithm Evonorm.

Results: Five case studies were performed.

Parameter estimation of a meal glucose-insulin model for TIDM patients from therapy historical data.

The effect of meal on blood glucose concentration is a key issue in diabetes mellitus because its estimation could be very useful in therapy decisions. In the case of type 1 diabetes mellitus (T1DM), the therapy based on automatic insulin delivery requires a closed-loop control system to maintain euglycaemia even in the postprandial state. Thus, the mathematical modelling of glucose metabolism is relevant to predict the metabolic state of a patient.

Hybrid BCI approach to control an artificial tibio-femoral joint.

Brain-Computer Interfaces (BCIs) for disabled people should allow them to use their remaining functionalities as control possibilities. BCIs connect the brain with external devices to perform the volition or intent of movement, regardless if that individual is unable to perform the task due to body impairments. In this work we fuse electromyographic (EMG) with electroencephalographic (EEG) activity in a framework called "Hybrid-BCI" (hBCI) approach to control the movement of a simulated tibio-femoral joint.